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Voltar para Manipulação de dados em escala: sistemas e algoritimos

Comentários e feedback de alunos de Manipulação de dados em escala: sistemas e algoritimos da instituição Universidade de Washington

4.3
estrelas
752 classificações
164 avaliações

Sobre o curso

Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively. The abstractions that emerged in the last decade blend ideas from parallel databases, distributed systems, and programming languages to create a new class of scalable data analytics platforms that form the foundation for data science at realistic scales. In this course, you will learn the landscape of relevant systems, the principles on which they rely, their tradeoffs, and how to evaluate their utility against your requirements. You will learn how practical systems were derived from the frontier of research in computer science and what systems are coming on the horizon. Cloud computing, SQL and NoSQL databases, MapReduce and the ecosystem it spawned, Spark and its contemporaries, and specialized systems for graphs and arrays will be covered. You will also learn the history and context of data science, the skills, challenges, and methodologies the term implies, and how to structure a data science project. At the end of this course, you will be able to: Learning Goals: 1. Describe common patterns, challenges, and approaches associated with data science projects, and what makes them different from projects in related fields. 2. Identify and use the programming models associated with scalable data manipulation, including relational algebra, mapreduce, and other data flow models. 3. Use database technology adapted for large-scale analytics, including the concepts driving parallel databases, parallel query processing, and in-database analytics 4. Evaluate key-value stores and NoSQL systems, describe their tradeoffs with comparable systems, the details of important examples in the space, and future trends. 5. “Think” in MapReduce to effectively write algorithms for systems including Hadoop and Spark. You will understand their limitations, design details, their relationship to databases, and their associated ecosystem of algorithms, extensions, and languages. write programs in Spark 6. Describe the landscape of specialized Big Data systems for graphs, arrays, and streams...

Melhores avaliações

HA
10 de Jan de 2016

Great course that strikes a balance between teaching general principles and concepts, and providing hands-on technical skills and practice.\n\nThe lessons are well designed and clearly conveyed.

WL
27 de Mai de 2016

I like the breadth of coverage of this class. Each of the exercise is a gem in that I get to learn something new also. I would highly recommend this even to experience practitioner also.

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26 — 50 de 160 Avaliações para o Manipulação de dados em escala: sistemas e algoritimos

por Killdary A d S

4 de Jul de 2019

Excelente curso, conteúdo fácil de entender e realmente desafiador. Recomendo para quem quer entender como é realizado a extração e análise de dados não estruturados.

por Leonid G

20 de Jun de 2017

Comprehensive and clear explanation of theory and interlinks of the up-to-date tools, languages, tendencies. Kudos and thanks to Bill Howe.

Highly recommended.

por Mahmoud M

18 de Jan de 2016

The course is very coherent and comprehensive. It covers only important aspects of the fields. Also, the exercises are very well prepared.

por Jun Q

8 de Ago de 2016

This is a quite wonderful course for large-scale data science. I believe I will have learned a lot via completing the courses.

por Karol O

22 de Dez de 2019

Engaging problemset makes sure that you will get your hands dirty with data. And that is great! Definitely worth your time.

por Roberto S

13 de Jun de 2017

Very good introduction to the topic; requires quite an effort to complete the assignments, but the outcome is worth it.

por Daniella B

21 de Abr de 2016

Lectures are great and well structured. Programming assignments are just amazing and interesting. Great course!

por Itai S

14 de Nov de 2015

הקורס נותן חשיפה טובה לכלי העבודה העדכניים. המשימות אינן פשוטות למשתמש המתחיל ודורשות התעמקות אך בהחלט אפשריות

por Achal K

5 de Fev de 2018

A very good introduction to skills needed for applying data science ideas on large scale data problems.

por Raheel H

1 de Jul de 2019

A great way to start, and become familiar with the nature, requirements & analytics of today's data.

por Bingcheng L

4 de Ago de 2019

Very very very tough for me. took me 3 months to finish.

But I learned so much from this course.

por Padam J T

7 de Ago de 2021

One of the best Data Science course I've ever taken anywhere. One should definitely go for it.

por Batt J

14 de Abr de 2018

Very good course for understanding the underlying logic behind emerging big data technologies

por Edwin A P V

12 de Dez de 2020

It's excellent. Important: Python Dev knowledge is a plus to complete the assignments.

por Usman

27 de Dez de 2016

A great course. I would just like more assignments and more information about spark.

por BI C

20 de Jan de 2016

Interesting course, good hands-on exercises. very useful course to practice python

por Kazım S

10 de Set de 2017

If you want to head into Data Science, this is a nice course that will help you.

por Daniel A

21 de Nov de 2015

This was a great course - well planned out and really informative. Thanks!

por Wonjun L

6 de Mar de 2016

If you are interested in data science then this course is the right one.

por Ahmed E

14 de Abr de 2017

Very good and informative course for data scientists and data engineers

por Asier

20 de Nov de 2015

Excellent overview of the Big Data field and its relation to eScience.

por Bruno F S

15 de Fev de 2016

Great course for those who want to know more about big data analysis.

por Muhammad A I

10 de Set de 2019

Love the the concept of "learning abstraction rather than tool".

por Gokhan C

28 de Mai de 2016

The assignments are really what make this course stand out.

por NothingElse

5 de Nov de 2015

speed is too fast, I can hard to keep pace with teacher's s